Systems and methods for determining an order collection start time

Abstract

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform receiving, at the one or more processors, an order from a customer electronic device; determining, using employee device data collected from one or more electronic devices of one or more employees of a store in a predictive analysis, an estimated collection time required for an employee of the one or more employees of the store to collect the one or more items of the order; receiving a check-in from an electronic device indicating that a pickup is en-route to pick-up the order; when the electronic device authorizes location tracking, tracking a location of the pickup after receiving the check-in from the electronic device; periodically determining, at one or more time intervals, an estimated travel time for the pickup to travel to the store from the location, as tracked; and when the estimated collection time is approximately equal in duration to the estimated travel time, coordinating displaying instructions for the employee of the store to begin collecting the one or more items of the order. Other embodiments are disclosed herein.

What is claimed is: 
     
       1. A system comprising:
 one or more processors; and 
 one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform functions comprising:
 receiving, by the one or more processors, an order from a customer electronic device; 
 determining, using a predictive analysis, an estimated collection time required for an employee of one or more employees of a store to collect one or more items of the order, wherein data used for the predictive analysis comprises employee device data collected from one or more electronic devices of the one or more employees of the store; 
 receiving, by the one or more processors, a mobile check-in from an electronic device indicating that a pickup is en-route to pick-up the order; 
 in response to receiving the mobile check-in, requesting, by the one or more processors, permission for location tracking from the electronic device; 
 when the electronic device authorizes the permission for the location tracking, tracking, by the one or more processors, a location of the pickup after receiving the mobile check-in from the electronic device; 
 periodically determining, by the one or more processors, an estimated travel time for the pickup to travel to the store from the location, as tracked; and 
 when the estimated collection time is approximately equal in duration to the estimated travel time, transmitting, by the one or more processors, a collection notification on a store interface of one of the one or more electronic devices of the employee of the store of the one or more employees of the store, wherein the collection notification comprises instructions for the employee of the store to begin collecting the one or more items of the order. 
 
 
     
     
       2. The system of  claim 1 , wherein:
 the predictive analysis comprises a regression analysis. 
 
     
     
       3. The system of  claim 1 , wherein the predictive analysis operates as a function of at least one of:
 one or more locations of the one or more items of the order; 
 a number of commodity switches required for the one or more employees to collect the one or more items of the order; 
 a historical performance of the employee assigned to collect the one or more items of the order; 
 a temperature sensitivity of at least one of the one or more items of the order; or 
 a time of day when the order is collected by the employee. 
 
     
     
       4. The system of  claim 1 , wherein the pickup comprises at least one of:
 a customer; 
 one or more employees; 
 a third party delivery service; 
 an autonomous vehicle; or 
 a drone. 
 
     
     
       5. The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform a function comprising:
 coordinating displaying vehicle information for the pickup on the electronic device of the employee of the one or more employees of the store. 
 
     
     
       6. The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform a function comprising:
 when the order has been collected by the employee, coordinating displaying a collected order notification on the customer electronic device, the collected order notification indicating that the order has been collected by the employee of the store. 
 
     
     
       7. The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform a function comprising:
 when the electronic device authorizes the permission for the location tracking, coordinating displaying an estimated pickup arrival time on at least the customer electronic device or the electronic device of the employee of the one or more employees. 
 
     
     
       8. The system of  claim 1 , wherein the predictive analysis comprises feature selection techniques. 
     
     
       9. The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform a function comprising:
 when the pickup delivers the order, coordinating displaying a delivery notification on the customer electronic device or the electronic device of the employee of the one or more employees. 
 
     
     
       10. The system of  claim 1 , wherein the predictive analysis comprises:
 determining, using the employee device data collected from the one or more electronic devices of the one or more employees of the store:
 one or more independent variables affecting the estimated collection time; 
 respective coefficients of each respective independent variable of the one or more independent variables affecting the estimated collection time; and 
 a constant applicable to historical picking data of the employee of the store. 
 
 
     
     
       11. A method being implemented via execution of computing instructions configured to run at one or more processors and stored at non-transitory computer-readable media, the method comprising:
 receiving, by the one or more processors, an order from a customer electronic device; 
 determining, using a predictive analysis, an estimated collection time required for an employee of one or more employees of a store to collect one or more items of the order, wherein data used for the predictive analysis comprises employee device data collected from one or more electronic devices of the one or more employees of the store; 
 receiving, by the one or more processors, a mobile check-in from an electronic device indicating that a pickup is en-route to pick-up the order; 
 in response to receiving the mobile check-in, requesting, by the one or more processors, permission for location tracking from the electronic device; 
 when the electronic device authorizes the permission for the location tracking, tracking, by the one or more processors, a location of the pickup after receiving the mobile check-in from the electronic device; 
 periodically determining, by the one or more processors, an estimated travel time for the pickup to travel to the store from the location, as tracked; and 
 when the estimated collection time is approximately equal in duration to the estimated travel time, transmitting, by the one or more processors, a collection notification on a store interface of one of the one or more electronic devices of the employee of the store of the one or more employees of the store, wherein the collection notification comprises instructions for the employee of the store to begin collecting the one or more items of the order. 
 
     
     
       12. The method of  claim 11 , wherein:
 the predictive analysis comprises a regression analysis. 
 
     
     
       13. The method of  claim 11 , wherein the predictive analysis operates as a function of at least one of:
 one or more locations of the one or more items of the order; 
 a number of commodity switches required for the one or more employees to collect the one or more items of the order; 
 a historical performance of the employee assigned to collect the one or more items of the order; 
 a temperature sensitivity of at least one of the one or more items of the order; or 
 a time of day when the order is collected by the employee. 
 
     
     
       14. The method of  claim 11 , wherein the pickup comprises at least one of:
 a customer; 
 one or more employees; 
 a third party delivery service; 
 an autonomous vehicle; or 
 a drone. 
 
     
     
       15. The method of  claim 11  further comprising:
 coordinating displaying vehicle information for the pickup on the electronic device of the employee of the one or more employees of the store. 
 
     
     
       16. The method of  claim 11  further comprising:
 when the order has been collected by the employee, coordinating displaying a collected order notification on the customer electronic device, the collected order notification indicating that the order has been collected by the employee of the store. 
 
     
     
       17. The method of  claim 11  further comprising:
 when the electronic device authorizes the permission for the location tracking, coordinating displaying an estimated pickup arrival time on at least the customer electronic device or the electronic device of the employee of the one or more employees. 
 
     
     
       18. The method of  claim 11 , wherein the predictive analysis comprises feature selection techniques. 
     
     
       19. The method of  claim 11  further comprising:
 when the pickup delivers the order, coordinating displaying a delivery notification on the customer electronic device or the electronic device of the employee of the one or more employees. 
 
     
     
       20. The method of  claim 11 , wherein the predictive analysis comprises:
 determining, using the employee device data collected from the one or more electronic devices of the one or more employees of the store:
 one or more independent variables affecting the estimated collection time; 
 respective coefficients of each respective independent variable of the one or more independent variables affecting the estimated collection time; and 
 
 a constant applicable to historical picking data of the employee of the store.